AI Engineer

Job Summary

Join our growing AI team to design, build and scale production-grade AI solutions across cloud and edge. You'll turn prototypes into reliable, low-latency services – owning data/feature pipelines, training/evaluation, deployment, monitoring and iteration. You'll optimize performance and cost; implement safety guardrails, observability and CI/CD/MLOps automations. You'll also enable edge/on-device inference (mobile, desktop, browser, IoT), including model packaging and compression, hardware acceleration (CPU/GPU/NPU), offline/real-time constraints, telemetry and OTA updates. Partner with data scientists, engineers and product to ship user-facing features quickly and safely in a fast-paced, collaborative environment.

Key Responsibilities

• Design, deploy, and optimize AI services, with models running in a self-hosted setupon cloud infrastructure.
• Build and maintain a centralized AI Gateway to manage multi-model access and routing
• Implement and evolve Agent-to-Agent (A2A) communication and the Model Context Protocol (MCP) for agent collaboration.
• Design and integrate a powerful Agent Memory System, including a dynamic knowledge base and contextual memory to empower intelligent behavior.
• Apply model optimization techniques to improve inference efficiency and cost-effectiveness.
• Develop and operate MLOps pipelines for model lifecycle management.
• Ensure system scalability, reliability and performance across diverse workloads.
• Collaborate across teams to bring intelligent agents into real-world applications.

Education, Qualifications and Skills:

• Education: Bachelor's degree/ Master's degree or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Electrical Engineering, or a related field.
• Minimum 3 years of experience in AI/ML/DL Engineer or similar roles.
• Strong programming skills in Python and experience with containerized and cloud-native environment.
• Solid understanding of AI/ML/DL model deployment, including serving, optimization, and context-aware design
• Experience in building systems with agent orchestration, memory management, and structured communication protocols
• Familiarity with retrieval-augmented generation, semantic memory, and message-driven workflows
• Hands-on experience working with GPU (NVIDIA) or TPU environments, including model quantization and other performance optimization techniques.
• Practical experience with MLOps pipelines for training, versioning, and deploying machine learning models
• Bonus: experience with agent-based architecture, LLM streaming patterns, Golang, and a strong foundation in mathematics, statistics, or linear algebra
• Skills:
• Strong problem-solving and analytical abilities.
• Excellent communication and collaboration skills.
• Ability to work independently and as part of a team.
• Fluency in English is a plus.

What we offer:

• Competitive salary and benefits package.
• Opportunity to work on a product that impacts millions of users.
• A dynamic and supportive work environment.
• Premium health insurance for you and your family.
• Professional growth and development opportunities.
• Annual leave 12 days per year + 1 Birthday Leave + 1 X'Mas
• Performance review: once per year
• Internal training/sharing and professional Training courses
• Team building, company trip, year end party, monthly activities,….
• Devices: Macbook and screen (If needed)
• Free tea and coffee
• Comfortable working Area
• Working hour: 9am – 6pm from Monday to Friday

Thank you for your interest in this opportunity and for taking the time to submit your application. Each application is carefully reviewed by our team. If your qualifications and experience align with the requirements of this position, a member of our recruitment team will be in contact with you within the next month.

Should the hiring team determine that your profile is not an ideal match for this particular role, we will retain your information for consideration in future recruitment efforts. We appreciate your understanding.